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OverviewJoin our SMB Engineering team and help us unlock the potential of the rapidly growing Small and Medium Business (SMB) segment.
Our SMB Engineering team is agile, creative, and determined to foster an experimentation culture.
Despite being a recent addition to the E+D family, we have the potential for expansive growth and impact.
Our responsibility is to accelerate M365 SMB Growth by creating fluid experiences for SMB customers through various channels.
We work collaboratively as a tight-knit unit, united behind a common objective, and are responsible for high-impact projects that have a direct impact on revenue.
With a focus on adopting an experimentation culture, we explore innovative approaches and embrace new ideas to release features that push boundaries.
We value individual growth, camaraderie, and having fun.On the SMB Data Engineering team, you will work with a team of other engineers and Data Scientist to grow and retain customers in the SMB M365 business.
You will play a crucial role in ensuring that data is at the heart of our efforts to grow and retain SMB customers using our M365 products.
Your work will directly impact our ability to provide valuable data insights, drive feature improvements, and ultimately enhance the SMB experience with M365.Microsoft's mission is to empower every person and every organization on the planet to achieve more.
As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals.
Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.QualificationsRequired Qualifications: Bachelor's Degree in Computer Science, or related field Experience in business analytics, data science, software development, data modeling or data engineering work or internship experience Experience in SQL, KQL, or other data manipulation languages.
Experience in working with various database systems, including relational databases (e.g., SQL Server, PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra).
Experience in programming languages like Python, Java, or C#.Other Requirements:Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
These requirements include but are not limited to the following specialized security screenings:Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.Preferred Qualifications: Understanding of data modeling techniques.
Experience in using version control systems like Git for tracking changes in code and configurations.
Familiarity of cloud computing environments such as Azure or Amazon Web Services (AWS) is a plus.Microsoft is an equal opportunity employer.
All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.ResponsibilitiesCreates reports and actionable business insight for SMB M365 purchases and usage.Collaborates with stakeholders, assesses data needs, and supports project cost evaluation.Supports the development of appropriate data models and pipelines for projects.Creates and reviews data dev specs.Assists in data modeling and design reviews, striving for improved usability and efficiency.Implements code for data extraction and basic transformations.Validates data quality and maintains source control and versioning.Contributes to data tool development and platform monitoring.Helps identify and address issues in data pipelines.Ensures compliance with data handling procedures.#LI-DNI
